European Actuarial Journal

, Volume 1, Issue 1, pp 131–157

Fast remote but not extreme quantiles with multiple factors: applications to Solvency II and Enterprise Risk Management

Authors

  • Matthieu Chauvigny
    • Milliman, Paris
  • Laurent Devineau
    • Milliman, Paris
    • Laboratoire SAF EA 2429, Institut de Science Financière et d’AssurancesUniversité de Lyon, Université Lyon 1
    • Laboratoire SAF EA 2429, Institut de Science Financière et d’AssurancesUniversité de Lyon, Université Lyon 1
  • Véronique Maume-Deschamps
    • Laboratoire SAF EA 2429, Institut de Science Financière et d’AssurancesUniversité de Lyon, Université Lyon 1
Original Research Paper

DOI: 10.1007/s13385-011-0034-0

Cite this article as:
Chauvigny, M., Devineau, L., Loisel, S. et al. Eur. Actuar. J. (2011) 1: 131. doi:10.1007/s13385-011-0034-0

Abstract

For operational purposes, in Enterprise Risk Management or in insurance for example, it may be important to estimate remote (but not extreme) quantiles of some function f of some random vector. The call to f may be time- and resource-consuming so that one aims at reducing as much as possible the number of calls to f. In this paper, we propose some ways to address this problem of general interest. We then numerically analyze the performance of the method on insurance and Enterprise Risk Management real-world case studies.

Keywords

Quantile estimation Risk factors Enterprise Risk Management Accelerated algorithm Nested Simulations

Copyright information

© DAV / DGVFM 2011